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Legal aspects of registration the time of cadastral data creation or modification / Joanna Reczyńska in Reports on geodesy and geoinformatics, vol 110 n° 1 (December 2020)
[article]
Titre : Legal aspects of registration the time of cadastral data creation or modification Type de document : Article/Communication Auteurs : Joanna Reczyńska, Auteur ; Pawel Hanus, Auteur Année de publication : 2020 Article en page(s) : pp 9 - 17 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cadastre étranger
[Termes IGN] base de données foncières
[Termes IGN] données cadastrales
[Termes IGN] droit foncier
[Termes IGN] enregistrement immobilier
[Termes IGN] INSPIRE
[Termes IGN] norme ISO
[Termes IGN] parcelle cadastrale
[Termes IGN] PologneRésumé : (auteur) In Poland, the cadastre is the basic register which is the source of information on cadastral entities and their property. Therefore, it should constitute a reliable source of information in the scope of establishing the range of law, its nature, but also the subject of its ownership. However, it is necessary to be able to not only check the current information on the legal status and its scope, but also review past statuses or determine the rights that will influence real estate in the future. The cadastre and related rights are changing very dynamically over time, and each state has a very strict reference to the previous state. Therefore, in order to manage real estate in the most effective way, it is necessary to record temporal attributes of cadastre objects. The main objective of this paper is to define the legal issues related to the possibility of registration at the time of creation or modification of object in the Polish cadastre. This paper includes analyses of both Polish legal regulations and European standards and norms. Moreover, the article presents the results of comparative analyses concerning the data model of cadastre and INSPIRE and Land Administration Domain Model (LADM) data models for the theme cadastral parcel in terms of temporal aspect. Numéro de notice : A2020-786 Affiliation des auteurs : non IGN Nature : Article DOI : 10.2478/rgg-2020-0007 Date de publication en ligne : 25/09/2020 En ligne : https://doi.org/10.2478/rgg-2020-0007 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96532
in Reports on geodesy and geoinformatics > vol 110 n° 1 (December 2020) . - pp 9 - 17[article]Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks / Felix Schiefer in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)
[article]
Titre : Mapping forest tree species in high resolution UAV-based RGB-imagery by means of convolutional neural networks Type de document : Article/Communication Auteurs : Felix Schiefer, Auteur ; Teja Kattenborn, Auteur ; Annett Frick, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 205-215 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage profond
[Termes IGN] arbre (flore)
[Termes IGN] carte forestière
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] espèce végétale
[Termes IGN] Forêt-Noire, massif de la
[Termes IGN] image à haute résolution
[Termes IGN] image captée par drone
[Termes IGN] image RVB
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier local
[Termes IGN] segmentation sémantique
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) The use of unmanned aerial vehicles (UAVs) in vegetation remote sensing allows a time-flexible and cost-effective acquisition of very high-resolution imagery. Still, current methods for the mapping of forest tree species do not exploit the respective, rich spatial information. Here, we assessed the potential of convolutional neural networks (CNNs) and very high-resolution RGB imagery from UAVs for the mapping of tree species in temperate forests. We used multicopter UAVs to obtain very high-resolution ( Numéro de notice : A2020-706 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.015 Date de publication en ligne : 03/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.015 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96236
in ISPRS Journal of photogrammetry and remote sensing > vol 170 (December 2020) . - pp 205-215[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2020121 RAB Revue Centre de documentation En réserve L003 Disponible Multistrategy ensemble regression for mapping of built-up density and height with Sentinel-2 data / Christian Geiss in ISPRS Journal of photogrammetry and remote sensing, vol 170 (December 2020)
[article]
Titre : Multistrategy ensemble regression for mapping of built-up density and height with Sentinel-2 data Type de document : Article/Communication Auteurs : Christian Geiss, Auteur ; Henrik Schrade, Auteur ; Patrick Aravena Pelizari, Auteur ; Hannes Taubenböck, Auteur Année de publication : 2020 Article en page(s) : pp 57-71 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Allemagne
[Termes IGN] apprentissage automatique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] hauteur du bâti
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] image TanDEM-X
[Termes IGN] modèle de régression
[Termes IGN] morphologie urbaine
[Termes IGN] pondération
[Termes IGN] processus gaussien
[Termes IGN] zone urbaine denseRésumé : (Auteur) In this paper, we establish a workflow for estimation of built-up density and height based on multispectral Sentinel-2 data. To do so, we render the estimation of built-up density and height as a supervised learning problem. Given the rational level of measurement of those two target variables, the regression estimation problem is regarded as finding the mapping between an incoming vector, i.e., ubiquitously available features computed from Sentinel-2 data, and an observable output (i.e., training set), which is derived over spatially limited areas in an automated manner. As such, training sets are automatically generated from a joint exploitation of TanDEM-X mission elevation data and Sentinel-2 imagery, and, as an alternative, from cadastral sources. The training sets are used to regress the target variables for spatial processing units which correspond to urban neighborhood scales. From a methodological point of view, we introduce a novel ensemble regression approach, i.e., multistrategy ensemble regression (MSER), based on advanced machine learning-based regression algorithms including Random Forest Regression, Support Vector Regression, Gaussian Process Regression, and Neural Network Regression. To establish a robust ensemble, those algorithms are learned with a modified version of the AdaBoost.RT algorithm. However, to reliably ensure diversity between single boosted regressors, we include a random feature subspace method in the procedure. In contrast to existing approaches, we selectively prune non-favorable regressors trained during the boosting procedure and calculate the final prediction by a weighted mean function on the residual models to ensure enhanced accuracy properties of predictions. Finally, outputs are concatenated into a single prediction with a decision fusion strategy. Experimental results are obtained from four test areas which cover the settlement areas of the four largest German cites, i.e., Berlin, Hamburg, Munich, and Cologne. The results unambiguously underline the beneficial properties of the MSER approach, since all best predictions were obtained with a boosted regressor in conjunction with a decision fusion strategy in a comparative setup. The mean absolute errors of corresponding models vary between 3 and 16% and 1–5.4 m with respect to built-up density and height, respectively, depending on the validation strategy, size of the spatial processing units, and test area. Also in a domain adaptation setup (i.e., when learning a model over a source domain and applying it over a geographically different target domain) numerous predictions show comparable accuracy levels as predictions obtained within a source domain. This further underlines the viability to transfer a model and, thus, enable a substitution of the training data in the target domains. Numéro de notice : A2020-704 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.004 Date de publication en ligne : 22/10/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.004 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96231
in ISPRS Journal of photogrammetry and remote sensing > vol 170 (December 2020) . - pp 57-71[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2020121 RAB Revue Centre de documentation En réserve L003 Disponible Semantic‐based urban growth prediction / Marvin Mc Cutchan in Transactions in GIS, Vol 24 n° 6 (December 2020)
[article]
Titre : Semantic‐based urban growth prediction Type de document : Article/Communication Auteurs : Marvin Mc Cutchan, Auteur ; Simge Özdal‐Oktay, Auteur ; Ioannis Giannopoulos, Auteur Année de publication : 2020 Article en page(s) : 1482 - 1503 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] apprentissage profond
[Termes IGN] croissance urbaine
[Termes IGN] dynamique spatiale
[Termes IGN] Europe (géographie politique)
[Termes IGN] information sémantique
[Termes IGN] modèle de simulation
[Termes IGN] modélisation spatiale
[Termes IGN] occupation du sol
[Termes IGN] OpenStreetMap
[Termes IGN] organisation spatiale
[Termes IGN] OWL
[Termes IGN] prévision
[Termes IGN] réseau neuronal artificiel
[Termes IGN] urbanisation
[Termes IGN] ville durableRésumé : (Auteur) Urban growth is a spatial process which has a significant impact on the earth’s environment. Research on predicting this complex process makes it therefore especially fruitful for decision‐making on a global scale, as it enables the introduction of more sustainable urban development. This article presents a novel method of urban growth prediction. The method utilizes geospatial semantics in order to predict urban growth for a set of random areas in Europe. For this purpose, a feature space representing geospatial configurations was introduced which embeds semantic information. Data in this feature space was then used to perform deep learning, which ultimately enables the prediction of urban growth with high accuracy. The final results reveal that geospatial semantics hold great potential for spatial prediction tasks. Numéro de notice : A2020-766 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12655 Date de publication en ligne : 14/07/2020 En ligne : https://doi.org/10.1111/tgis.12655 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96657
in Transactions in GIS > Vol 24 n° 6 (December 2020) . - 1482 - 1503[article]Stand-level mortality models for Nordic boreal forests / Jouni Siipilehto in Silva fennica, vol 54 n° 5 (December 2020)
[article]
Titre : Stand-level mortality models for Nordic boreal forests Type de document : Article/Communication Auteurs : Jouni Siipilehto, Auteur ; Micky Allen, Auteur ; Urban Nilsson, Auteur ; Andreas Brunner, Auteur ; et al., Auteur ; Urban Nilsson Année de publication : 2020 Article en page(s) : n° 10414 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] âge du peuplement forestier
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle de simulation
[Termes IGN] modélisation de la forêt
[Termes IGN] mortalité
[Termes IGN] Norvège
[Termes IGN] régression logistique
[Termes IGN] Suède
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) New mortality models were developed for the purpose of improving long-term growth and yield simulations in Finland, Norway, and Sweden and were based on permanent national forest inventory plots from Sweden and Norway. Mortality was modelled in two steps. The first model predicts the probability of survival, while the second model predicts the proportion of basal area in surviving trees for plots where mortality has occurred. In both models, the logistic function was used. The models incorporate the variation in prediction period length and in plot size. Validation of both models indicated unbiased mortality rates with respect to various stand characteristics such as stand density, average tree diameter, stand age, and the proportion of different tree species, Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.), and broadleaves. When testing against an independent dataset of unmanaged spruce-dominated stands in Finland, the models provided unbiased prediction with respect to stand age. Numéro de notice : A2020-854 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article DOI : 10.14214/sf.10414 Date de publication en ligne : 01/12/2020 En ligne : https://doi.org/10.14214/sf.10414 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98710
in Silva fennica > vol 54 n° 5 (December 2020) . - n° 10414[article]The crown condition of Norway spruce and occurrence of symptoms caused by Armillaria spp. in mixed stands / Petr Čermák in Journal of forest science, vol 66 n° 12 (December 2020)PermalinkThe utility of fused airborne laser scanning and multispectral data for improved wind damage risk assessment over a managed forest landscape in Finland / Ranjith Gopalakrishnan in Annals of Forest Science, vol 77 n° 4 (December 2020)PermalinkTree mortality in the dynamics and management of uneven-aged Norway spruce stands in southern Finland / Sauli Valkonen in European Journal of Forest Research, vol 139 n° 6 (December 2020)PermalinkVisualization of 3D property data and assessment of the impact of rendering attributes / Stefan Seipel in Journal of Geovisualization and Spatial Analysis, vol 4 n° 2 (December 2020)PermalinkAdaptation de l'irrigation au changement climatique dans l'Union européenne : les actions engagées par les États membres pour économiser l'eau / Claire Serra-Wittling in Sciences, eaux & territoires, n° 34 (novembre 2020)PermalinkAnalyzing the joint effect of forest management and wildfires on living biomass and carbon stocks in Spanish forests / Patricia Adame in Forests, vol 11 n°11 (November 2020)PermalinkBretagne, la végétation cartographiée / Marielle Mayo in Géomètre, n° 2185 (novembre 2020)PermalinkCadastral development in Norway: the need for improvement / Leiv Bjarte Mjøs in Survey review, vol 52 n° 375 (November 2020)PermalinkDecentralized markets and the emergence of housing wealth inequality / Omar A. Guerrero in Computers, Environment and Urban Systems, vol 84 (November 2020)PermalinkEvaluating geo-tagged Twitter data to analyze tourist flows in Styria, Austria / Johannes Scholz in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)PermalinkGood things take time : Diversity effects on tree growth shift from negative to positive during stand development in boreal forests / Tommaso Jucker in Journal of ecology, vol 108 n° 6 (November 2020)PermalinkMapping the fantastic great Southern continent, 1760–1777: A study in enlightenment geography / Vanessa Collingridge in Cartographic journal (the), Vol 57 n° 4 (November 2020)PermalinkStreets of London: Using Flickr and OpenStreetMap to build an interactive image of the city / Azam Raha Bahrehdar in Computers, Environment and Urban Systems, vol 84 (November 2020)PermalinkUrban tree species identification and carbon stock mapping for urban green planning and management / MD Abdul Choudhury in Forests, vol 11 n°11 (November 2020)PermalinkAssessing the effects of thinning on stem growth allocation of individual Scots pine trees / Ninni Saarinen in Forest ecology and management, vol 474 ([15/10/2020])PermalinkAtmospheric pathways and distance range analysis of castanea pollen transport in Southern Spain / Rocio López-Orozco in Forests, vol 11 n° 10 (October 2020)PermalinkBoreal peatland forests: ditch network maintenance effort and water protection in a forest rotation framework / Jenny Miettinen in Canadian Journal of Forest Research, vol 50 n° 10 (October 2020)PermalinkCombined InSAR and terrestrial structural monitoring of bridges / Sivasakthy Selvakumaran in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)PermalinkComparing features of single and multi-photon lidar in boreal forests / Xiaowei Yu in ISPRS Journal of photogrammetry and remote sensing, vol 168 (October 2020)PermalinkGoing to the Finnish line / Hannu Heinonen in GEO: Geoconnexion international, vol 19 n° 6 (October 2020)PermalinkIncreasing Cervidae populations have variable impacts on habitat suitability for threatened forest plant and lichen species / James D.M. Speed in Forest ecology and management, vol 473 ([01/10/2020])PermalinkLa méthode de la photo-interview à partir de la photographie aérienne : Le cas d’un bidonville à Nanterre dans les années 1960 / Laetitia Delavoipiere in EchoGeo, n° 54 (octobre - décembre 2020)PermalinkSpatio-temporal relationship between land cover and land surface temperature in urban areas: A case study in Geneva and Paris / Xu Ge in ISPRS International journal of geo-information, vol 9 n° 10 (October 2020)PermalinkStudy on the inter-annual hydrology-induced deformations in Europe using GRACE and hydrological models / Artur Lenczuk in Journal of applied geodesy, vol 14 n° 4 (October 2020)PermalinkThe 2018–2019 seismo-volcanic crisis east of Mayotte, Comoros islands: seismicity and ground deformation markers of an exceptional submarine eruption / Anne Lemoine in Geophysical journal international, vol 223 n° 1 (October 2020)PermalinkTowards an optimization of sample plot size and scanner position layout for terrestrial laser scanning in multi-scan mode / Tim Ritter in Forests, vol 11 n° 10 (October 2020)PermalinkTowards dynamic forest trafficability prediction using open spatial data, hydrological modelling and sensor technology / Aura Salmivaara in Forestry, an international journal of forest research, vol 93 n° 5 (October 2020)PermalinkUrban flooding in Britain: an approach to comparing ancient and contemporary flood exposure / T.E. O'Shea in Natural Hazards, Vol 104 n° 1 (October 2020)PermalinkA spatio-temporal web-application for the understanding of the formation of the Parisian metropolis / Emile Blettery in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol VI-4/W1 ([03/09/2020])PermalinkAncient forest statistics provide centennial perspective over the status and dynamics of forest area in France / Timothée Audinot in Annals of Forest Science, vol 77 n° 3 (September 2020)PermalinkArctic tsunamis threaten coastal landscapes and communities – survey of Karrat Isfjord 2017 tsunami effects in Nuugaatsiaq, western Greenland / Mateusz C. Strzelecki in Natural Hazards and Earth System Sciences, vol 20 n° 9 (September 2020)PermalinkAssessing local trends in indicators of ecosystem services with a time series of forest resource maps / Matti Katila in Silva fennica, vol 54 n° 4 (September 2020)PermalinkAssessment of landslide susceptibility at a local spatial scale applying the multi-criteria analysis and GIS: a case study from Slovakia / Jana Vojteková in Geomatics, Natural Hazards and Risk, vol 11 n° 1 (2020)PermalinkChloroplast haplotypes of Northern red oak (Quercus rubra L.) stands in Germany suggest their origin from Northeastern Canada / Jeremias Götz in Forests, vol 11 n° 9 (September 2020)PermalinkClimate–growth relationships at the transition between Fagus sylvatica and Pinus mugo forest communities in a Mediterranean mountain / Chiara Calderano in Annals of Forest Science, vol 77 n° 3 (September 2020)PermalinkCO2 fertilization, transpiration deficit and vegetation period drive the response of mixed broadleaved forests to a changing climate in Wallonia / Louis de Wergifosse in Annals of Forest Science, vol 77 n° 3 (September 2020)PermalinkDeriving a frozen area fraction from Metop ASCAT backscatter based on Sentinel-1 / Helena Bergstedt in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)PermalinkEvaluating the accuracy of ALS-based removal estimates against actual logging data / Ville Vähä-Konka in Annals of Forest Science, vol 77 n° 3 (September 2020)PermalinkMapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth Engine / Aparna R. Phalke in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)PermalinkPhysical, chemical and mechanical wood properties of Pinus nigra growing in Portugal / Alexandra Dias in Annals of Forest Science, vol 77 n° 3 (September 2020)PermalinkUse of Bayesian modeling to determine the effects of meteorological conditions, prescribed burn season, and tree characteristics on litterfall of pinus nigra and pinus pinaster stands / Juncal Espinosa in Forests, vol 11 n° 9 (September 2020)PermalinkUse of non-destructive test methods on Irish hardwood standing trees and small-diameter round timber for prediction of mechanical properties / Daniel F. Llana in Annals of Forest Science, vol 77 n° 3 (September 2020)PermalinkUsing OpenStreetMap data and machine learning to generate socio-economic indicators / Daniel Feldmeyer in ISPRS International journal of geo-information, vol 9 n° 9 (September 2020)PermalinkVehicle detection of multi-source remote sensing data using active fine-tuning network / Xin Wu in ISPRS Journal of photogrammetry and remote sensing, vol 167 (September 2020)PermalinkSemCity Toulouse: a benchmark for building instance segmentation in satellite images / Ribana Roscher in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-5-2020 (August 2020)PermalinkAmbiguous use of geographical information systems for the rectification of large-scale geometric maps / Anders Wästfelt in Cartographic journal (the), Vol 57 n° 3 (August 2020)PermalinkPermalinkGuided feature matching for multi-epoch historical image blocks pose estimation / Lulin Zhang in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)PermalinkModeling soil erosion after mechanized logging operations on steep terrain in the Northern Black Forest, Germany / Julian Haas in European Journal of Forest Research, vol 139 n°4 (August 2020)PermalinkA name‐led approach to profile urban places based on geotagged Twitter data / Juntao Lai in Transactions in GIS, Vol 24 n° 4 (August 2020)PermalinkPredicting biomass dynamics at the national extent from digital aerial photogrammetry / Bronwyn Price in International journal of applied Earth observation and geoinformation, vol 90 (August 2020)PermalinkReintroduction of the European bison (Bison bonasus) in central-eastern Europe: a case study / Cathlin M. Lord in International journal of geographical information science IJGIS, vol 34 n° 8 (August 2020)PermalinkCan we characterize river corridor evolution at a continental scale from historical topographic maps? A first assessment from the comparison of four countries / J. Horacio Garcia in River Research and Applications, vol 36 n° 6 (July 2020)PermalinkCartographie des surfaces pastorales à l’aide des données Sentinel 2 L3A et des données ouvertes : Promesses et réalités / Urcel Kalenga Tshingomba in Revue internationale de géomatique, vol 30 n° 3-4 (juillet - décembre 2020)PermalinkClassification of hyperspectral and LiDAR data using coupled CNNs / Renlong Hang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)PermalinkEcology and management of northern red oak (Quercus rubra L. syn. Q. borealis F. Michx.) in Europe: a review / Valeriu-Norocel Nicolescu in Forestry, an international journal of forest research, vol 93 n° 4 (July 2020)PermalinkImproved crop classification with rotation knowledge using Sentinel-1 and -2 time series / Sébastien Giordano in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 7 (July 2020)PermalinkObjets connectés et mobilité urbaine : visualiser les déplacements des usagers de Twitter avec des graphes dynamiques / Françoise Lucchini in Mappemonde, n° 128 (juillet 2020)PermalinkThe impact of drought on total ozone flux in a mountain Norway spruce forest / Thomas Agyei in Journal of forest science, vol 66 n° 7 (juillet 2020)PermalinkThe impact of terrestrial gravity data density on geoid accuracy: case study Bilogora in Croatia / Olga Bjelotomić Oršulić in Survey review, vol 52 n° 373 (July 2020)PermalinkTriangulation network of 1929–1944 of the first 1:500 urban map of València / Miriam Villar-Cano in Survey review, vol 52 n° 373 (July 2020)PermalinkWhat influences the long-term development of mixtures in British forests? / William L. Mason in Forestry, an international journal of forest research, vol 93 n° 4 (July 2020)PermalinkAnalysing the quality of Swiss National Forest Inventory measurements of woody species richness / Berthold Traub in Forest ecosystems, vol 7 (2020)PermalinkA century of National Forest Inventory in Norway – informing past, present, and future decisions / Johannes Breidenbach in Forest ecosystems, vol 7 (2020)PermalinkDiscriminant analysis for lodging severity classification in wheat using RADARSAT-2 and Sentinel-1 data / Sugandh Chauhan in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkEstimating spatio-temporal air temperature in London (UK) using machine learning and earth observation satellite data / Rochelle Schneider dos Santos in International journal of applied Earth observation and geoinformation, vol 88 (June 2020)PermalinkFine-grained landuse characterization using ground-based pictures: a deep learning solution based on globally available data / Shivangi Srivastava in International journal of geographical information science IJGIS, vol 34 n° 6 (June 2020)PermalinkHydrogeology of the western Po plain (Piedmont, NW Italy) / Domenico Antonio De Luca in Journal of maps, vol 16 n° 2 ([01/06/2020])PermalinkImproving precision of field inventory estimation of aboveground biomass through an alternative view on plot biomass / Christoph Kleinn in Forest ecosystems, vol 7 (2020)PermalinkMapping aboveground biomass and its prediction uncertainty using LiDAR and field data, accounting for tree-level allometric and LiDAR model errors / Svetlana Saarela in Forest ecosystems, vol 7 (2020)PermalinkMapping forest age using National Forest Inventory, airborne laser scanning, and Sentinel-2 data / Johannes Schumacher in Forest ecosystems, vol 7 (2020)PermalinkModelling housing rents using spatial autoregressive geographically weighted regression: a case study in cracow, Poland / Mateusz Tomal in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)PermalinkProfitability of growing Scots pine on cutaway peatlands / Lasse Aro in Silva fennica, vol 54 n° 3 (June 2020)PermalinkStand growth and structure of mixed-species and monospecific stands of Scots pine (Pinus sylvestris L.) and oak (Q. robur L., Quercus petraea (MATT.) LIEBL.) analysed along a productivity gradient through Europe / Hans Pretzsch in European Journal of Forest Research, vol 139 n° 3 (June 2020)PermalinkUnder-canopy UAV laser scanning for accurate forest field measurements / Eric Hyyppä in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkUnderstanding governance dynamics: The governing system of spatial data infrastructures / Jaap-Willem Sjoukema in International Journal of Spatial Data Infrastructures Research, vol 15 (Year 2020)PermalinkValidation of Sentinel-3A SRAL coastal sea level data at high posting rate: 80 Hz / Ana Aldarias in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)PermalinkMethodology of the automatic generalization of buildings, road networks, forests and surface waters: a case study based on the Topographic Objects Database in Poland / Izabela Karsznia in Geocarto international, vol 35 n° 7 ([15/05/2020])PermalinkAssessment of the accuracy of DTM river bed model using classical surveying measurement and LiDAR: a case study in Poland / Pawel Kotlarz in Survey review, vol 52 n° 372 (May 2020)PermalinkCity information modeling, Rennes s'offre un jumeau numérique / Marielle Mayo in Géomètre, n° 2180 (mai 2020)PermalinkComment cartographier l’occupation du sol en vue de modéliser les réseaux écologiques ? Méthodologie générale et cas d’étude en Île-de-France / Chloé Thierry in Sciences, eaux & territoires, article hors-série n° 65 (mai 2020)PermalinkIncorporating landscape character in cork oak forest expansion in Sardinia: constraint or opportunity? / I.N. Vogiatzakis in Forests, vol 11 n° 5 (May 2020)PermalinkIntertidal topography mapping using the waterline method from Sentinel-1 & -2 images: The examples of Arcachon and Veys Bays in France / Edward Salameh in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)PermalinkShrub biomass estimates in former burnt areas using Sentinel 2 images processing and classification / Jose Aranha in Forests, vol 11 n° 5 (May 2020)PermalinkThe evolution of cadastral systems in Austria and Galicia (Poland): different approaches to a similar system from a common beginning / Józef Hernik in Cartographic journal (the), Vol 57 n° 2 (May 2020)PermalinkDeformation detection through the realization of reference frames / Nestoras Papadopoulos in Journal of applied geodesy, vol 14 n° 2 (April 2020)PermalinkDetection of Xylella fastidiosa infection symptoms with airborne multispectral and thermal imagery: Assessing bandset reduction performance from hyperspectral analysis / T. Poblete in ISPRS Journal of photogrammetry and remote sensing, vol 162 (April 2020)PermalinkGenetic variation of introduced red oak (Quercus rubra) stands in Germany compared to North American populations / Tim Pettenkofer in European Journal of Forest Research, vol 139 n° 2 (April 2020)PermalinkMultitemporal analysis of gully erosion in olive groves by means of digital elevation models obtained with aerial photogrammetric and LIDAR data / Tomás Fernández in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)PermalinkSize-class structure of the forests of Finland during 1921–2013: a recovery from centuries of exploitation, guided by forest policies / Helena M. Henttonen in European Journal of Forest Research, vol 139 n° 2 (April 2020)PermalinkStreet-Frontage-Net: urban image classification using deep convolutional neural networks / Stephen Law in International journal of geographical information science IJGIS, vol 34 n° 4 (April 2020)Permalink3D laser scanning of the natural caves: Example of Škocjanske jame / Richard Walters in Geodetski vestnik, Vol 64 n° 1 (March - May 2020)PermalinkAn original method for tree species classification using multitemporal multispectral and hyperspectral satellite data / Olga Grigorieva in Silva fennica, vol 54 n° 2 (March 2020)PermalinkCan mixed pine forests conserve understory richness by improving the establishment of understory species typical of native oak forests? / Daphne Lopez-Marcos in Annals of Forest Science, Vol 77 n° 1 (March 2020)PermalinkComparison and analysis of results of 3D modelling of complex cultural and historical objects using different types of terrestrial laser scanner / Admir Mulahusic in Survey review, vol 52 n° 371 (March 2020)Permalink